Gemini 4 Carbon vs. mainstream models

Model A

Model B

Gemini 4 CarbonReady

The answer will appear here

Choose models and send one question below.

Gemini 4 ArgonReady

The answer will appear here

Choose models and send one question below.

Test question: Concurrent payment and stock: find the root cause

Task: review an order handler under concurrency and crashes, then propose a verifiable repair.
Input pseudocode:
async handle(e):
  if await db.seen(e.id): return
  await pay.charge(e.order, e.amount)
  await stock.reserve(e.sku, 1)
  await db.mark_seen(e.id)
Conditions: each order has one logical charge event, delivered concurrently or repeatedly. The process can crash immediately after a successful charge. Insufficient stock raises an error. Payment supports a durable idempotency key and lookup by that key. Database transactions exclude payment and stock. Stock idempotency is unspecified; no refund API is supplied.
Output, in order: (1) two concrete failure interleavings and their wrong outcomes; (2) minimal repair pseudocode or a state machine specifying event/order keys, durable states and recovery from an unknown payment outcome; (3) three tests, each with event order and expected invariants; (4) missing stock/refund contracts. Distinguish duplicate-charge prevention from atomic order fulfillment. Do not assume a database transaction makes external operations atomic, invent APIs, or claim execution. Use at most 300 words excluding code.

One question, sent to both models. Each comparison starts a fresh response. Up to 3,000 input bytes. Ctrl / ⌘ + Enter to send.

Selected reasoning models use supported low effort; other selections keep direct-answer mode. The 1,024-token cap includes thinking and may leave an incomplete answer. This is not a high-effort benchmark.

Model capability and use-case comparison

Eight models across six vendors. Carbon is the latest Gemini 4 release, Argon a same-generation baseline, and 3.8 Flash the current Flash option. Qwen3.8 Max Prime and Grok 4.7 add two independent vendor choices. Checked November 11, 2026.

Model	Official capability and evidence	Tasks worth trying	Serving and page limits
Gemini 4 Carbon	Complex reasoning, coding and scientific problem solving. Official docs	Audit a small defect; propose a minimal fix and checks.	Text/image route; Google’s broader tool environment is not reproduced here.
Gemini 4 Argon	Google positions Argon for faster responses and lower token spend than Carbon. Official docs	Re-run a proven prompt and measure whether Carbon reduces rework.	Same route context limit as Carbon; not proof of equal reasoning quality.
Gemini 3.8 Flash	Google’s latest general-purpose Flash text model; speed/cost-oriented engineering and agents. Documentation	Run all five compact tasks as a cost-sensitive baseline.	Text/image route; the page does not expose the vendor’s tools or media inputs.
GPT-6.1 Sol	OpenAI model for complex coding and professional workflows. Documentation	Compare root-cause repairs and evidence-grounded decisions.	Low reasoning is supported; official tool calling requires Responses, not this text trial.
Claude Fable 5.2	Demanding reasoning and long agent sessions; adaptive thinking is always on. Official docs	Compare constraint adherence and evidence in a compact analysis.	A short answer cap cannot reproduce Max-effort agent benchmarks.
Kimi K3.1 Pro	Official guide emphasizes coding, 3D creation and long-horizon agents. Official docs	Try Chinese requirements extraction and a code-review checklist.	This is Pro, not Highspeed or a cluster configuration; text trial only.
Qwen3.8 Max Prime	High-throughput Qwen Max variant for coding, structured outputs and long-context analysis. Documentation	Compare defect fixes and evidence extraction under identical inputs.	Low effort on this page; no vendor tools or video input.
Grok 4.7	Flagship for software engineering, agents and professional knowledge work. Documentation	Compare failure analysis, math and constraint adherence.	Low effort on this page; vendor xhigh benchmark scores are a different setting.

QVeris model specifications

Model	Context tokens	Max output tokens	Route inputs
Gemini 4 Carbon	1,048,576	943,718	image, text
Gemini 4 Argon	1,048,576	943,718	image, text
Gemini 3.8 Flash	1,048,576	65,536	image, text
GPT-6.1 Sol	1,050,000	128,000	image, text
Claude Fable 5.2	1,000,000	128,000	file, image, text
Kimi K3.1 Pro	1,048,576	1,048,576	image, text
Qwen3.8 Max Prime	1,000,000	131,072	image, text
Grok 4.7	500,000	450,000	image, text

QVeris public catalog snapshot: November 11. Limits and supported endpoints describe the route; they do not imply all input/output maxima can be used together. Google’s default synchronous Carbon output cap is 65,536, while this route lists 943,718.

QVeris Model Gateway: capabilities and integration

Use QVeris to compare models across providers and connect your selected model to an application or agent. Filter the catalog by capabilities, input formats, context limits and Credits pricing before choosing a model. Browse the model catalog

Gateway capability	How it helps your workflow
One API key and endpoint	Use a QVeris API key with the OpenAI-compatible base URL `https://aigateway.qveris.ai/v1`.
Multiple client protocols	Chat Completions, Responses, Messages and Embeddings are available when supported by the selected model.
Capability-based model selection	Check `GET /v1/models` for public model IDs and supported capabilities before switching models.
Streaming and usage records	Receive streaming output and billing information; retain the call ID to correlate usage and troubleshoot requests.

Compare catalog prices before calling; use the final QVeris usage record to reconcile actual Credits. Supported interfaces and parameters vary by model. Model Gateway documentation

Multi-model API pricing and usage costs

QVeris retail Credits per million tokens; all eight models and published tiers, checked November 11, 2026. Sol’s route tier starts at 272,000 input tokens and Grok’s at 200,000. Cache prices apply only to actual hits.

Model	Input token range	Input	Output	Cached input
Gemini 4 Carbon	0+	1,050	5,250	52.5
Gemini 4 Argon	0+	1,050	5,250	52.5
Gemini 3.8 Flash	0+	433.125	2,165.625	43.3125
GPT-6.1 Sol	0–271,999	1,050	5,250	52.5
GPT-6.1 Sol	272,000+	2,100	7,875	105
Claude Fable 5.2	0+	4,200	21,000	105
Kimi K3.1 Pro	0+	1,015.9275	5,314.1025	101.5875
Qwen3.8 Max Prime	0+	2,100	6,300	262.5
Grok 4.7	0–199,999	1,050	3,150	262.5
Grok 4.7	200,000+	2,100	6,300	525

Assume 1,000 uncached input tokens + 200 billed output tokens, without tools or request fees: Carbon and Argon each cost (1,000 × 1,050 + 200 × 5,250) / 1,000,000 = 2.10 Credits; Fable 5.2 costs 8.40; Kimi K3.1 Pro costs 2.078748. Same usage does not mean the models will produce the same token count. With the same uncached 1,000-input / 200-output assumption, Flash 3.8 costs 0.86625 Credits and Sol costs 2.10 Credits in its first tier.

With 800 cached and 200 uncached input tokens plus 200 output tokens, Carbon’s example is (800 × 52.5 + 200 × 1,050 + 200 × 5,250) / 1,000,000 = 1.302 Credits. These are usage examples, not paid-run receipts; reasoning and other billable usage may change the final amount.

Google API prices in USD

Carbon service	Through Nov 30: in / out / cache	From Dec 1: in / out / cache
Standard	$2 / $10 / $0.10	$4 / $20 / $0.20
Batch / Flex	$1 / $5 / $0.05	$2 / $10 / $0.10
Priority	$3.60 / $18 / $0.18	$7.20 / $36 / $0.36

USD per million tokens; dates are in 2026. Thinking tokens are billed as output. Implicit caching only; no explicit caching. Search/Maps have a shared monthly allowance of 5,000 requests per service, then $14/1,000; one user request can trigger multiple queries. Full pricing and limits. These vendor services are not options in the comparison below. Credits are not USD.

Gemini 4 Carbon: strengths and use cases

Carbon is Google’s reasoning model for difficult debugging, multi-step engineering and scientific investigation. Argon is the closer everyday-work baseline; Carbon is worth evaluating when extra investigation and verification can improve the deliverable. Public release

Google announced Carbon on October 28 and opened public access on November 10, 2026. The QVeris public catalog lists gemini-4-carbon with text/image input and text output. Account admission and a successful request are separate from a catalog listing.

The page uses low reasoning for Carbon, Argon, Flash, Sol, Fable, Qwen and Grok; Kimi keeps its direct-answer mode. Each side allows up to 1,024 output tokens and 3,000 input bytes. Generated code is displayed, not executed.

Look for three practical differences: a repair that handles failure ordering, a conclusion with evidence and unknowns separated, and a reproducible artifact instead of an unsupported completion claim. These are selection criteria; no model is assumed to win every task.

Native multimodal and tool support

Google’s native API accepts text, images, video, audio and PDF, and returns text. It supports function calling, structured outputs, code execution, computer use, file search, Search/Maps grounding and URL context. Image/audio generation and Live API are not supported.

These are native API capabilities. The QVeris catalog route and this text-only comparison have separate input and tool limits. Official documentation

Thinking levels: quality and cost trade-offs

Level	When to try it
`low`	Simple analysis and cost-sensitive work; difficult tasks may lose quality.
`medium`	Native default; a balanced starting point for coding and agent tasks.
`high`	Hard reasoning, science and code; more thinking tokens and a slower first response.

Compare the same task across levels and choose the lowest setting that meets your acceptance criteria. This page uses low; its results do not represent the native default or high. Official documentation

Gemini 4 Carbon: benchmarks and real cases

Official evaluations and author-reported work are separated from the five adapted questions. The adapted questions have not been rerun for new scores in this revision. Keep environment, reasoning settings and missing comparator outputs visible.

What the original release evaluations show

The model card preserves October 2026 results. Google reports Gemini scores at highest thinking, pass@1 unless noted; smaller tests may average trials. Other vendors’ numbers are generally self-reported. Cyber scores describe Fairwind access. Evaluation methodology

Evaluation	Gemini 4 Argon	Gemini 4 Carbon	Difference	Interpretation
Terminal-Bench 4.0 (AA)	57.1%	65.2%	+8.1 pp	Terminal engineering tasks; higher is better.
GraphWalks · 256k–1M BFS F1	84.2%	96.2%	+12.0 pp	Long-context graph reasoning, not all document tasks.
FrontierSWE 2	55.0%	61.2%	+6.2 pp	Carbon still trails GPT-6 Astra (65.5%).
OSWorld 2.1 · offline subset	74.7%	81.5%	+6.8 pp	Carbon still trails Claude Opus 5.5 (87.2%).

Google model card and original results · pp = percentage points. These are separate tests, not a combined ranking.

Independent evaluations: exact model and settings

Snapshot checked November 11, 2026. CursorBench uses multi-file tasks from real Cursor sessions. The current leaderboard does not expose a task count; sample size is N/A. Costs below belong to Cursor’s test environment.

Benchmark / setting	Carbon	Comparator	What it tells you
CursorBench 4.0 · High	60.4% · $9.22	Argon High: 52.9% · $4.57	+7.5 pp; higher task cost than Argon.
CursorBench 4.0 · Medium	60.1% · $8.49	Fable 5.2 Max: 60.0% · $32.79	Different effort levels; no significance claim.
AA Intelligence Index v5.0.1	60 · High	Fable 5.2 Max (default fallback): 65	A composite score, not an accuracy percentage. Kimi K3.1 Pro: N/A in this snapshot.

Cursor leaderboard · AA Carbon profile · AA version and methodology. The earlier “59, #1” claim was an October v5.0 snapshot and is not the current ranking.

Official evaluations: Argon → Carbon

View official evaluations · View official demos

Terminal-Bench 4.0 (AA)

Gemini 4 Argon57.1%

Gemini 4 Carbon65.2%

+8.1 pp · Terminal engineering tasks; higher is better.

October 2026; highest thinking unless noted.

GraphWalks · 256k–1M BFS F1

Gemini 4 Argon84.2%

Gemini 4 Carbon96.2%

+12.0 pp · Long-context graph reasoning, not all document tasks.

October 2026; highest thinking unless noted.

Core capabilities and corresponding evidence

Engineering: combine the terminal scores with a small patch-and-test task. Long context: require traceable references across supplied documents. Creative coding: Google’s campus game uses Antigravity, Blender and Three.js; the community film below also needs an execution/rendering environment. A text response alone is not a rendered application.

Community tests: outputs and limitations

Task / input	Carbon result	Comparator result	Difference and judgment	View
Procedural 4K short film; task summary, not a disclosed full prompt.	Author reports a two-minute Blender film using OpenCode 2.2.7; a camera-shake bug needed manual repair.	The post praises improvement over Argon but provides no matched Argon output.	Evidence of a workflow and a concrete failure, not a measured model ranking. Render time and GPU cost are not inference latency or QVeris Credits.	Original result u/proomptengineer
Engineering audit and analytical modeling; reported task categories.	A commenter reports false completion claims and repeated schema guesses at High.	The same commenter prefers Argon High; no paired raw logs or complete prompts were supplied.	Unverified experience report. Use it to design acceptance checks, not as proof of a general regression.	Original discussion u/ApaaGames

Community outcomes are reported by their authors. These selected cases are not an exhaustive survey or a QVeris rerun. Missing same-task outputs remain missing.

Five built-in challenges and acceptance criteria

Challenge	Evidence behind the task	What a good answer must show	Source
Concurrent payment and stock: find the root cause	Official multi-system debugging and root-cause investigation	Two failure interleavings; stable payment idempotency; durable workflow state; compensation and recovery tests.	Original evidence
File download: prevent path escape	Official vulnerability analysis and root-cause patches; defensive review only	Resolved path containment, link boundary, useful tests and an explicit TOCTOU limitation.	Original evidence
Conflicting documents: cite facts and preserve unknowns	Official document analysis and structured knowledge-work artifacts	Apply S2 precedence; RMB 600,000 ceiling, RMB 420,000 committed; no invented launch date or security sign-off.	Original evidence
3D animation: repair camera jitter	Author-reported Blender short film and manual camera-shake repair	No cumulative state; random frame access is deterministic; fade and amplitude constraints are testable.	Original evidence
Experiment analysis: detect aggregation bias	Official scientific reasoning and data analysis; synthetic checkable data	Stratified and pooled rates, 50/50 standardization, confounding and a falsifiable follow-up design.	Original evidence

Gemini 4 Carbon: usage guide and FAQ

Long-output configuration and context limits

Input, thinking and output share 1,048,576 tokens. A standard response defaults to 65,536 thinking-plus-output tokens. Long decode requires a higher max_output_tokens and background execution or client continuation; a large context limit alone does not enable it.

Use it when one hard reasoning or coding response needs more room. Short Q&A, extraction and latency-sensitive tasks usually do not need it. The page’s 1,024-token trial limit remains separate. Official documentation

How should I evaluate an answer?

These five challenges need human or tool-assisted review. Check the acceptance criteria, run generated code only in an appropriate sandbox, and record incomplete answers separately. The page does not assign an automatic accuracy score to these tasks.

Why can only one side fail?

Requests are independent. Admission, output limits or upstream errors can affect one model. Keep the other answer and partial output; a failed or truncated request is not an incorrect-answer score. No automatic retries.

What does “model unverified” mean?

A returned identifier differs from the selected model or identity evidence is missing. Keep the answer and actual charges, but suspend scoring until an exact documented mapping is established.

What is charged, and when?

Opening the page, switching languages or changing questions does not send inference. Sending uses your account. Credits show actual settlement; missing settlement stays pending. Average tok/s includes waiting and network time. Stopping does not imply a refund.

Can this page run code, images or a full agent?

It accepts text and displays text. Generated code is not executed. Official tools, multimedia input and long decode require a separately configured application and do not follow automatically from catalog capability tags.

Why do old articles say Carbon is number one?

The October release cited AA v5.0 at 59. This article separates that dated release from the current v5.0.1 snapshot and from CursorBench. Rankings and effort settings change; use the linked original leaderboard.

Gemini 4 Carbon: Pricing, Real Cases & Model Capability Comparison